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crcrpar / torch_compile_hopper_blackwell_analysis.md
Created December 4, 2025 15:18
torch.compile Feature Completeness on Hopper & Blackwell: Comprehensive Analysis of TMA and Advanced GPU Features

torch.compile Feature Completeness on Hopper & Blackwell: A Comprehensive Analysis

Author: Generated via Claude analysis of PyTorch codebase
Date: December 4, 2025
Focus: Understanding TMA and advanced features for H100/B100/B200 GPUs


Executive Summary

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crcrpar / bash_strict_mode.md
Created April 1, 2022 22:04 — forked from mohanpedala/bash_strict_mode.md
set -e, -u, -o, -x pipefail explanation
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crcrpar / how-gradients-are-accumulated-in-real.ipynb
Created March 21, 2021 00:05
how-gradients-are-accumulated-in-real.ipynb
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crcrpar / how-gradients-are-accumulated-in-real.ipynb
Created March 21, 2021 00:03
how-gradients-are-accumulated-in-real.ipynb
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diff --git a/torchvision/datasets/mnist.py b/torchvision/datasets/mnist.py
index e87cd46e..bfd59914 100644
--- a/torchvision/datasets/mnist.py
+++ b/torchvision/datasets/mnist.py
@@ -131,6 +131,11 @@ class MNIST(VisionDataset):
def class_to_idx(self) -> Dict[str, int]:
return {_class: i for i, _class in enumerate(self.classes)}
+ def _check_raw_data_exists(self) -> bool:
+ return all([
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